#loc3])\0Amodule {\0A  func.func @host_func(%arg0: tensor<3360x?xi32> loc(fused[#loc1, #loc2, #loc3]), %arg1: tensor<3xi32> loc(fused[#loc1, #loc2, #loc3]), %arg2: tensor<i32> loc(fused[#loc1, #loc2, #loc3]), %arg3: tensor<2xi32> loc(fused[#loc1, #loc2, #loc3])) -> (tensor<1x1120x?xi32>, tensor<1x1120x?xi32>, tensor<1120x?xi32>, tensor<2xi32>) {\0A    %0 = \22tf.Reshape\22(%arg0, %arg1) {_xla_outside_compilation = \220\22} : (tensor<3360x?xi32>, tensor<3xi32>) -> tensor<3x1120x?xi32> loc(#loc9)\0A    %1:3 = ...

  %3 = "tf.Reshape"(%2, %cst_2) {device = ""} : (tensor<64x8x64xf32>, tensor<2xi32>) -> tensor<512x64xf32>

  func.return %3 : tensor<512x64xf32>

  // CHECK-DAG: %[[CST_0:.*]] = "tf.Const"() <{value = dense<[2, 0, 1]> : tensor<3xi32>}> : () -> tensor<3xi32>
  // CHECK-DAG: %[[CST_1:.*]] = "tf.Const"() <{value = dense<3> : tensor<i32>}> : () -> tensor<i32>

}

func.func @"__inference_Dataset_map_<lambda>_80"(%arg0: tensor<*xi32>) -> tensor<*xi32> {
  %0 = "tf.Const"() {value = dense<2> : tensor<i32>} : () -> tensor<i32>
  %1 = "tf.Mul"(%arg0, %0) {device = ""} : (tensor<*xi32>, tensor<i32>) -> tensor<*xi32>
  %2 = "tf.Identity"(%1) {device = ""} : (tensor<*xi32>) -> tensor<*xi32>
  func.return %2 : tensor<*xi32>
}

}

func.func @"__inference_Dataset_map_<lambda>_80"(%arg0: tensor<*xi32>) -> tensor<*xi32> {
  %0 = "tf.Const"() {value = dense<2> : tensor<i32>} : () -> tensor<i32>
  %1 = "tf.Mul"(%arg0, %0) {device = ""} : (tensor<*xi32>, tensor<i32>) -> tensor<*xi32>
  %2 = "tf.Identity"(%1) {device = ""} : (tensor<*xi32>) -> tensor<*xi32>
  func.return %2 : tensor<*xi32>
}

func.func @main() -> tensor<2x3xi32> {
  %graph = tf_executor.graph {
    %0:2 = tf_executor.island wraps "tf.Const"() {value = dense<5> : tensor<2x3xi32>} : () -> tensor<2x3xi32> loc("Const0")
    %1:2 = tf_executor.island wraps "tf.Const"() {value = dense<4.2> : tensor<4x5xf32>} : () -> tensor<4x5xf32> loc("Const1")

  %2 = "tfl.pseudo_const"() {value = dense<[1, 384, 128]> : tensor<3xi32>} : () -> tensor<3xi32>
  %3 = "tfl.reshape"(%1, %2) {tac.device = "CPU", tac.inference_type = "QUANTIZED_INT8"} : (tensor<384x128x!quant.uniform<i8:f32, 0.9:-4>>, tensor<3xi32>) -> tensor<1x384x128x!quant.uniform<i8:f32, 0.9:-4>>

func.func @main(%arg0: tensor<10xi32>, %arg1: tensor<10xi32>) -> tensor<10xi32>
attributes {tf.entry_function = {inputs = "input0,input1", outputs = "Add"}} {
  %graph = tf_executor.graph {
    %2:2 = tf_executor.island wraps "tf.Add"(%arg0, %arg1) {T = "tfdtype$DT_INT32", device = ""} : (tensor<10xi32>, tensor<10xi32>) -> tensor<10xi32> loc("Add")
    tf_executor.fetch %2 : tensor<10xi32>
  }
  func.return %graph : tensor<10xi32>
}

  %cst_2 = arith.constant dense<[4, 1024, 4096]> : tensor<3xi32>
  %0 = "tfl.fully_connected"(%arg0, %cst_0, %cst_1) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<4x1024x1024xbf16>, tensor<4096x1024xbf16>, none) -> tensor<4096x4096xbf16>
  %1 = "tfl.reshape"(%0, %cst_2) : (tensor<4096x4096xbf16>, tensor<3xi32>) -> tensor<4x1024x4096xbf16>
  func.return %1 : tensor<4x1024x4096xbf16>

      %outputs_9, %control_10 = tf_executor.island(%control_4) wraps "tf.Identity"(%outputs_7) {device = ""} : (tensor<2x3xi32>) -> tensor<2x3xi32>
      tf_executor.fetch %outputs_9 : tensor<2x3xi32>
    }
    return %0 : tensor<2x3xi32>
  }
}

// CHECK: module attributes
// CHECK-SAME:  tfl.metadata = {{{.*}}keep_stablehlo_constant = "true"{{.*}}}

    %4:2 = tf_executor.island wraps "tf.Add"(%arg0, %3) {T = "tfdtype$DT_INT32", device = ""} : (tensor<10xi32>, tensor<10xi32>) -> tensor<10xi32> loc("Add")
    tf_executor.fetch %4#0 : tensor<10xi32>
  }
  func.return %graph : tensor<10xi32>
}

// CHECK: name: "foo"
// CHECK-NEXT: op: "_Arg"
// CHECK: name: "bar"